WiFi based indoor location technologies have attracted a lot of attention in the past decade given the wide deployment of WLAN infrastructure. At present there are several industry efforts underway to develop technology to determine mobile device locations basing on WiFi signal strength (e.g., RSSI). In one example WiFi RSSI may be used to estimate mobile device distance from the known locations of Access Points, which can then be used to pinpoint device location using trilateration techniques. In another example WiFi RSSI is employed as a “fingerprint” measurement, in which the mobile device location is estimated through WiFi signal measurements from multiple access points, which signal measurements are matched against a pre-calibrated fingerprint data set for a given location. Thus, if the set of RSSI WiFi signals reported by a mobile device matches a given fingerprint data set, the mobile device can be pinpointed at the location associated with the fingerprint data set.
However, each of these techniques is subject to error due to a phenomenon that is termed herein “device diversity.” The term device diversity refers to the general situation in which different mobile devices and in particular different device models can report different RSSI readings given the same received reference signal. In other words, two different devices positioned at the exact same location at the same time that are receiving the same radio signal(s) may report different RSSI information. In general, the RSSI reading is affected by transceiver design, radio calibration, antenna placement, etc. Thus, the accuracy of determination of location based upon RSSI information may vary among different devices, such that any locationing system that uses RSSI information to determine location generates a less robust determination of device location as a whole.
It is with respect to these and other considerations that the present improvements have been needed.